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Machines
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Selected Papers from Conference on Control, Mechatronics and Automation (ICCMA)
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Selected Papers from Conference on Control, Mechatronics and Automation (ICCMA)

A special issue of Machines (ISSN 2075-1702).

Deadline for manuscript submissions: closed (28 February 2019) | Viewed by 20026

Special Issue Editor

Prof. Dr. Genci Capi

E-Mail Website
Guest Editor
Assistive Robotics Laboratory, Department of Mechanical Engineering, Faculty of Science and Engineering, Hosei University, Kajino-cho 3-7-2, Koganei-shi, Tokyo 184-8584, Japan
Interests: intelligent robots with a focus on brain-machine interface; evolutionary robotics; map building; multi-robot systems; humanoid robot
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

2018 The 6th International Conference on Control, Mechatronics, and Automation (http://www.iccma.org) will be held in Tokyo, Japan on October 12–14, 2018.  It is supported by the International Association of Computer Science & Information Technology.

ICCMA 2013 was held in Sydney (Australia); ICCMA 2014 was held in Dubai (UAE); ICCMA 2015 and ICCMA 2016 were both held in Barcelona (Spain); and ICCMA 2017 was held in University of Alberta, Edmonton, Canada. Furthermore, ICCMA 2019 has been announced to be held in TU Delft, Netherlands.

It covers a wide range of fields in mechanical engineering and aims to bring together engineering technology expertise. Suitable topics include, but are not limited to, the following:

  • Intelligent mechatronics, robotics, biomimetic, automation, and control systems
  • Biomedical and rehabilitation engineering, prosthetics, and artificial organs
  • Control system modeling, and simulation techniques and methodologies
  • AI, intelligent control, neuro-control, fuzzy control, and their applications
  • Industrial automation, process control, manufacturing processes, and automation
  • The application of hydraulic technology
  • Fault diagnosis and troubleshooting of hydraulic systems
  • The design and use of hydraulic servo systems
  • Electromechanical transmission control

Bearing in mind the significance of mechanical control, intelligent mechatronics, and automation, in general, this Special Issue focuses on the recent development of various fields or cross-fields of related topics, and it represents a good opportunity for researchers around the world to disseminate different aspects of their work.

ICCMA2018 will follow up the success of past conferences by bringing together researchers and application developers from different areas focusing on unifying themes. We invite investigators to contribute original research articles to the conference, as well as to the Special Issue.

Prof. Dr. Genci Capi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligent mechatronics
  • robotics
  • biomimetics
  • automation
  • control systems
  • manufacturing process

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Published Papers (4 papers)

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Research

18 pages, 4745 KiB  
Article
Reduced Order Controller Design for Symmetric, Non-Symmetric and Unstable Systems Using Extended Cross-Gramian
by Muhammad Raees Furquan Azhar, Umair Zulfiqar, Muwahida Liaquat and Deepak Kumar
Machines 2019, 7(3), 48; https://doi.org/10.3390/machines7030048 - 29 Jun 2019
Cited by 1 | Viewed by 2862
Abstract
In model order reduction and system theory, the cross-gramian is widely applicable. The cross-gramian based model order reduction techniques have the advantage over conventional balanced truncation that it is computationally less complex, while providing a unique relationship with the Hankel singular values of [...] Read more.
In model order reduction and system theory, the cross-gramian is widely applicable. The cross-gramian based model order reduction techniques have the advantage over conventional balanced truncation that it is computationally less complex, while providing a unique relationship with the Hankel singular values of the original system at the same time. This basic property of cross-gramian holds true for all symmetric systems. However, for non-square and non-symmetric dynamical systems, the standard cross-gramian does not satisfy this property. Hence, alternate approaches need to be developed for its evaluation. In this paper, a generalized frequency-weighted cross-gramian-based controller reduction algorithm is presented, which is applicable to both symmetric and non-symmetric systems. The proposed algorithm is also applicable to unstable systems even if they have poles of opposite polarities and equal magnitudes. The proposed technique produces an accurate approximation of the reduced order model in the desired frequency region with a reduced computational effort. A lower order controller can be designed using the proposed technique, which ensures closed-loop stability and performance with the original full order plant. Numerical examples provide evidence of the efficacy of the proposed technique. Full article
(This article belongs to the Special Issue Selected Papers from Conference on Control, Mechatronics and Automation (ICCMA))
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12 pages, 269 KiB  
Article
Spectrum of Elementary Cellular Automata and Closed Chains of Contours †
by Alexander Tatashev and Marina Yashina
Machines 2019, 7(2), 28; https://doi.org/10.3390/machines7020028 - 30 Apr 2019
Cited by 18 | Viewed by 3188
Abstract
In this paper, we study the properties of some elementary automata. We have obtained the characteristics of these cellular automata. The concept of the spectrum for a more general class than the class of elementary automata is introduced. We introduce and study discrete [...] Read more.
In this paper, we study the properties of some elementary automata. We have obtained the characteristics of these cellular automata. The concept of the spectrum for a more general class than the class of elementary automata is introduced. We introduce and study discrete dynamical systems which represents the transport of mass on closed chains of contours. Particles on contours move in accordance with given rules. These dynamical systems can be interpreted as cellular automata. Contributions towards this study are as follows. The characteristics of some elementary cellular automata have been obtained. A theorem about the velocity of particles’ movement on the closed chain has been proved. It has been proved that, for any ε > 0 , there exists a chain with flow density ρ < ε such that the average flow particle velocity is less than the velocity of free movement. An interpretation of this system as a transport model is given. The spectrum of a binary closed chain with some conflict resolution rule is studied. Full article
(This article belongs to the Special Issue Selected Papers from Conference on Control, Mechatronics and Automation (ICCMA))
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31 pages, 2710 KiB  
Article
Adaptive Robust Vehicle Motion Control for Future Over-Actuated Vehicles
by Moad Kissai, Bruno Monsuez, Xavier Mouton, Didier Martinez and Adriana Tapus
Machines 2019, 7(2), 26; https://doi.org/10.3390/machines7020026 - 19 Apr 2019
Cited by 8 | Viewed by 5886
Abstract
Many challenges still need to be overcome in the context of autonomous vehicles. These vehicles would be over-actuated and are expected to perform coupled maneuvers. In this paper, we first discuss the development of a global coupled vehicle model, and then we outline [...] Read more.
Many challenges still need to be overcome in the context of autonomous vehicles. These vehicles would be over-actuated and are expected to perform coupled maneuvers. In this paper, we first discuss the development of a global coupled vehicle model, and then we outline the control strategy that we believe should be applied in the context of over-actuated vehicles. A gain-scheduled H ∞ controller and an optimization-based Control Allocation algorithms are proposed. High-fidelity co-simulation results show the efficiency of the proposed control logic and the new possibilities that could offer. We expect that both car manufacturers and equipment suppliers would join forces to develop and standardize the proposed control architecture for future passenger cars. Full article
(This article belongs to the Special Issue Selected Papers from Conference on Control, Mechatronics and Automation (ICCMA))
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14 pages, 3752 KiB  
Article
Deep Learning-Based Landmark Detection for Mobile Robot Outdoor Localization
by Sivapong Nilwong, Delowar Hossain, Shin-ichiro Kaneko and Genci Capi
Machines 2019, 7(2), 25; https://doi.org/10.3390/machines7020025 - 18 Apr 2019
Cited by 43 | Viewed by 7353
Abstract
Outdoor mobile robot applications generally implement Global Positioning Systems (GPS) for localization tasks. However, GPS accuracy in outdoor localization has less accuracy in different environmental conditions. This paper presents two outdoor localization methods based on deep learning and landmark detection. The first localization [...] Read more.
Outdoor mobile robot applications generally implement Global Positioning Systems (GPS) for localization tasks. However, GPS accuracy in outdoor localization has less accuracy in different environmental conditions. This paper presents two outdoor localization methods based on deep learning and landmark detection. The first localization method is based on the Faster Regional-Convolutional Neural Network (Faster R-CNN) landmark detection in the captured image. Then, a feedforward neural network (FFNN) is trained to determine robot location coordinates and compass orientation from detected landmarks. The second localization employs a single convolutional neural network (CNN) to determine location and compass orientation from the whole image. The dataset consists of images, geolocation data and labeled bounding boxes to train and test two proposed localization methods. Results are illustrated with absolute errors from the comparisons between localization results and reference geolocation data in the dataset. The experimental results pointed both presented localization methods to be promising alternatives to GPS for outdoor localization. Full article
(This article belongs to the Special Issue Selected Papers from Conference on Control, Mechatronics and Automation (ICCMA))
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